Abstract: Nowadays blind/referenceless image spatial quality evaluator (BRISQUE) based on natural scene statistics is one of the state-of-the-art no-reference algorithms. But it only analyzes the original image and ignores the difference of the features constructed. Here an improved algorithm BRISQUEs is proposed and implemented by three steps. First, we apply mean subtracted contrast normalized to the gradient images and construct a new feature vector to assess quality. Second, we weight some key features of BRISQUE to improve assessment. After the two assessments obtained, a further average is made to weaken the bias from different assessments. Through the experiments on the LIVE IQA database, our approach has a remarkable performance than previous no-reference algorithms and is statistically superior to the popular multi-scale structural similarity index.

Key words: no-reference image quality assessment, natural scene statistics, gradient image, key feature